Ensemble learning for air quality index prediction: integrating gradient boosting, XGBoost, and stacking with SHAP-based interpretability
Abstract The increasing challenge of air pollution in cities requires smart methods to make proper predictions and manage the problem. Although machine learning and deep learning models have contributed greatly to weather and pollution forecasting, the main issue is the real-time flexibility, and sc...
I tiakina i:
| Ngā kaituhi matua: | , , , , , |
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| Hōputu: | Artigo |
| Reo: | Inglês |
| I whakaputaina: |
Nature Portfolio
2026-02-01
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| Rangatū: | Scientific Reports |
| Ngā marau: | |
| Urunga tuihono: | https://doi.org/10.1038/s41598-026-39232-w |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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